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Normalized Similarity of RNA Sequences

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String Processing and Information Retrieval (SPIRE 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3772))

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Abstract

We introduce a normalized version of the LCS metric as a new local similarity measure for comparing two RNAs. An \(\mathcal{O}(n^{2}m{\rm lg}m)\) time algorithm is presented for computing the maximum normalized score of two RNA sequences, where n and m are the lengths of the sequences and n ≤ m. This algorithm has the same time complexity as the currently best known global LCS algorithm.

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Author information

Authors and Affiliations

  1. Institute of Computer Science, Friedrich-Schiller Universität Jena, Jena Center for Bioinformatics, Germany

    Rolf Backofen

  2. Department of Computer Science, University of Haifa, Israel

    Danny Hermelin & Oren Weimann

  3. Department of Computer Science, University of Haifa, Haifa, Israel

    Gad M. Landau

  4. Department of Computer and Information Science, Polytechnic University, New York, USA

    Gad M. Landau

Authors
  1. Rolf Backofen
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  2. Danny Hermelin
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  3. Gad M. Landau
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  4. Oren Weimann
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Editor information

Editors and Affiliations

  1. University of Toronto,  

    Mariano Consens

  2. Dept. of Computer Science, University of Chile,  

    Gonzalo Navarro

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© 2005 Springer-Verlag Berlin Heidelberg

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Backofen, R., Hermelin, D., Landau, G.M., Weimann, O. (2005). Normalized Similarity of RNA Sequences. In: Consens, M., Navarro, G. (eds) String Processing and Information Retrieval. SPIRE 2005. Lecture Notes in Computer Science, vol 3772. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11575832_40

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  • DOI: https://doi.org/10.1007/11575832_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29740-6

  • Online ISBN: 978-3-540-32241-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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